Three session guides get you started with data warehousing at IBM Insight at World of Watson

Join us October 24 to 27, 2016 in Las Vegas!

by Cindy Russell, IBM Data Warehouse marketing

IBM Insight has been the premiere data management and analytics event for IBM analytics technologies, and 2016 is no exception.  This year, IBM Insight is being hosted along with World of Watson and runs from October 24 to 27, 2016 at the Mandalay Bay in Las Vegas, Nevada.  It includes 1,500 sessions across a range of technologies and features keynotes by IBM President and CEO, Ginni Rometty; Senior Vice President of IBM Analytics, Bob Picciano; and other IBM Analytics and industry leaders.  Every year, we include a little fun as well, and this year the band is Imagine Dragons.

IBM data warehousing sessions will be available across the event as well as in the PureData System for Analytics Enzee Universe (Sunday, October 23).  Below are product-specific quick reference guides that enable you to see at a glance key sessions and activities, then plan your schedule.  Print these guides and take them with you or put the links to them on your phone for reference during the conference.

This year, the Expo floor is called the Cognitive Concourse, and we are located in the Monetizing Data section, Cognitive Cuisine experience area.  We’ll take you on a tour across our data warehousing products and will have some fun as we do it, so please stop by.  There is also a demo room where you can see live demos and engage with our technical experts, as well as a series of hands-on labs that let you experience our products directly.

The IBM Insight at World of Watson main web page is located here.  You can register and then use the agenda builder to create your personalized schedule.

IBM PureData System for Analytics session reference guide

Please find the session quick reference guide for PureData System for Analytics here: ibm.biz/wow_enzee

Enzee Universe is a full day of dedicated PureData System for Analytics / Netezza sessions that is held on Sunday, October 23, 2016.  To register for Enzee Universe, select sessions 3459 and 3461 in the agenda builder tool.  This event is open to any full conference pass holder.

During the regular conference, there are also more than 35 PureData, Netezza, IBM DB2 Analytics Accelerator for z/OS (IDAA) technical sessions across all the conference tracks, as well as hands on labs.  There are several session being presented by IBM clients so you can see how they put PureData System for Analytics to use.  Click the link above to see the details.

IBM dashDB Family session reference guide

Please find the session quick reference guide for the dashDB family here: ibm.biz/wow_dashDB

There are a more than 40 sessions for dashDB, including a “Meet the Family” session that will help you become familiar with new products in this family of modern data management and data warehousing tools.  There is also a “Birds of a Feather” panel discussion on Hybrid Data Warehousing, and one that describes some key use cases for dashDB.  And, you can also see a demo, take in a short theatre session or try out a hands-on lab.

IBM BigInsights, Hadoop and Spark session reference guide

Please find the session quick reference guide for BigInsights, Hadoop and Spark topics here: ibm.biz/wow_biginsights

There are more than 65 sessions related to IBM BigInsights, Hadoop and Spark, with several hands on labs and theatre sessions. There is everything from an Introduction to Data Science to Using Spark for Customer Intelligence Analytics to hybrid cloud data lakes to client stories of how they use these technologies.

Overall, it is an exciting time to be in the data warehousing and analytics space.  This conference represents a great opportunity to build depth on IBM products you already use, learn new data warehousing products, and look across IBM to learn completely new ways to employ analytics—from Watson to Internet of Things and much more.  I hope to see you there.

What’s new: Netezza Platform Software and INZA software for PureData Systems for Analytics

by Doug Dailey

The IBM PureData Systems for Analytics team has just released a new set of enhancements over current software versions of Netezza Platform Software (NPS), INZA and IBM Fluid Query. These include enhanced  integration, security, real-time analytics for z Systems and usability features, all included in our latest software suite that has been posted on Fix Central.

There will be something here for everyone, whether you are looking to increase security, gain more leverage with DB2 Analytics Accelerator for z/OS*, improve your day-to-day experience or integrate PureData System (Netezza technology) into a Logical Data Warehouse. This post covers the new capabilities and enhancements in NPS 7.2.1 and INZA 3.2.1 software.  Refer to my IBM Fluid Query 1.6 post  for more information.

Strengthening end-to-end security for PureData and DB2 Analytics Accelerator for z/OS

With the advent of self-encrypted disk drives in our N3001 model, we laid the groundwork for securing data at rest. Not only do you have state of the art disk encryption keys by Seagate and Hitachi at work from a hardware standpoint, but you also have added peace of mind through a second tier of security that protects host drives and those drives associated with the Snippet Processing Unit. A local keystore with flexible CLI on the N3001 system enabled you to protect your most valuable assets. This release adds support for KMIP, which now allows 3rd party and IBM targeted key management software to backup, store and manage host and SPU keys on your system. Additional attention was paid to hardening the host systems for the DB2 Analytics Accelerator powered by PureData.
security

Speaking of DB2 Analytics Accelerator, this release of NPS provides key functionality recently added to DB2 Analytics Accelerator in version 5.1 which incorporates Netezza Analytics as a core component to help accelerate the use of predictive analytics applications (e.g., SPSS) such as data mining and in-database modeling. By extending support for the mainframe EBCDIC code to INZA software with support for new sets of procedures, you can run real-time analytics on DB2 Analytics Accelerator and establish work areas for data scientists. In-database transformation supports IBM DataStage balanced optimization and ETL/ELT consolidation processing.

This optimized, integrated appliance has been hardened to not only support self-encrypting drives available through PureData Systems for Analytics N3001 systems, but it now accounts for encryption of data-in-motion by encrypting network with the mainframe, FIPS-enabled RHEL, LFTP and secure VPN. Updated performance around continuous load operations better supports enterprise clients running highly concurrent trickle-feed loads under heavy processing of simultaneous mixed workloads to ensure faster data synchronization and TTV for insights. EBCDIC support for Netezza Analytics provides the ability to execute sophisticated in-database algorithms on DB2 Analytics Accelerator that allow micro-analytics across transactional, historical and real-time data.  NPS software now supports the following algorithms: Decision Tree, Regression Tree, Naïve Bayes, K-means Clustering and Two-Step Clustering.

PureData IDAA images

Making life easier through an improved User Experience

If these aren’t enough, we also targeted some areas to improve overall user experience by providing tooling and support that will make life easier for DBAs, system administrators and application developers:

  • Improved throughput and consistency for trickle-feed and highly concurrent smaller load operations.
  • nzload enhancements reduce TTV and shorten ETL activities; recordDelimiter, newline, timestamp, merge, datedelim, timedelim, and monitor.
  • New merge capability improves RI and positions Oracle migrations to PureData System.
  • nzSQL for Windows greatly improves usability for managing PureData System from the Windows desktop environment.
  • nzSQL support for external remote tables allows users to run load/unload operations from Linux clients to/from a remote file rather than host-only loads.
  • PureData will natively support Microsoft .NET and open a new range of possibilities for partner solutions.
  • JDBC support for JDK 1.7. in both NPS and INZA software ensures support for latest Hadoop distributions and also for Fluid Query.
  • New 64-bit BNR connectors are now certified for the latest versions of Tivoli, Netbackup and EMC.
  • PureData improves uptime by reducing requirements to stop and start NPS when user connections are exceeded.
  • ODBC support is now available for comments through DSN, odbc.ini and connection string (single, multi, inline, nested comments), as well as support for the LIMIT clause.

SQL enhancements

We’ve incorporated support for newer Client Kit OS versions and platforms with this release. Support for Windows 8, Windows 2012 R2, Ubuntu, and a completely new Power PC RHEL client for Little Endian. Support for Power on Little Endian positions PureData Systems for IBM BigInsights and the IBM Open Platform. We have also included additional SQL support for:

  • Support for DROP TABLE IF EXISTS
  • CREATE TABLE IF NOT EXISTS
  • Single slice support for JOINS with multi-column distribution keys
  • SQL push-down of NULL aware
  • New table-based Zone Maps

Client download of these new releases

NPS 7.2.1 and INXA 3.2.1 software is available at no charge to existing PureData clients. It can be easily downloaded from IBM Support Fix Central. Note that business partners and prospective clients can download and explore these new releases on Netezza Developer Network (additional information below).

fluid query download from fix central

Packaging and distribution

From a packaging perspective we refreshed IBM Netezza Platform Developer Software to this latest NPS 7.2.1 release to ensure the software suite is current from IBM’s Passport Advantage.

Supported Appliances Supported Software
  • N3001
  • N2002
  • N2001
  • N100x
  • C1000
  • Netezza Platform Software v7.2.1
  • Netezza Client Kits v7.2.1
  • Netezza SQL Extension Toolkit v7.2.1
  • Netezza Analytics v3.2.1
  • IBM Fluid Query v1.6
  • Netezza Performance Portal v2.1.1
  • IBM Netezza Platform Development Software v7.2.1

For the Netezza Developer Network we continue to expand the ability to easily pick up and work with non-warranted products for basic evaluation by refreshing the Netezza Emulator to NPS 7.2.1 with INZA 3.2.1. You will find a refresh of our non-warranted version of Fluid Query 1.6 and the complete set of Client Kits that support NPS 7.2.1.

NDN download button

Feel free to download and play with these as a prelude to PureData Systems for Analytics purchase or as a quick way to validate new software functionality with your application. We maintain our commitment to business partners working with our systems by maintaining the latest systems and software for you to access. Bring your application or solution and work to certify, qualify and validate them.

For additional information on Fluid Query 1.6, refer to my what’s new post.

* DB2 Analytics Accelerator for z/OS is a high-performance appliance that integrates the IBM z Systems infrastructure with IBM PureData™ for Analytics, powered IBM Netezza technology. The solution transforms your mainframe into a highly-efficient transactional and analytics processing environment. This enables clients to exploit z Systems data where it originates.

Doug Daily About Doug,
Doug has over 20 years combined technical & management experience in the software industry with emphasis in customer service and more recently product management.He is currently part of a highly motivated product management team that is both inspired by and passionate about the IBM PureData System for Analytics product portfolio.

What’s new: IBM Fluid Query 1.6

by Doug Dailey

Editorial Note: IBM Fluid Query 1.7 became available in May, 2016. You can read about features in release 1.6 here, but we also recommend reading the release 1.7 blog here.

The IBM PureData Systems for Analytics team has assembled a value-add set of enhancements over current software versions of Netezza Platform Software (NPS), INZA software and Fluid Query. We have enhanced  integration, security, real-time analytics for System z and usability features with our latest software suite arriving on Fix Central today.

There will be something here for everyone, whether you are looking to integrate your PureData System (Netezza) into a Logical Data Warehouse, improve security, gain more leverage with DB2 Analytics Accelerator for z/OS, or simply improve your day-to-day experience. This post covers the IBM Fluid Query 1.6 technology.  Refer to my NPS and INZA post (link) for more information on the enhancements that are now available in these other areas.

Integrating with the Logical Data Warehouse: Fluid Query overview

Are you struggling with building out your data reservoir, lake or lagoon? Feeling stuck in a swamp? Or, are you surfing effortlessly through an organized Logical Data Warehouse (LDW)?

Fluid Query offers a nice baseline of capability to get your PureData footprint plugged into your broader data environment or tethered directly to your IBM BigInsights Apache Hadoop distribution. Opening access across your broader ecosystem of on-premise, cloud, commodity hardware and Hadoop platforms gets you ever closer to capturing value throughout “systems of engagement” and “systems of record” so you can reveal new insights across the enterprise.

Now is the time to be fluid in your business, whether it is ease of data integration, access to key data for discovery/exploration, monetizing data, or sizing fit-for-purpose stores for different data types.  IBM Fluid Query opens these conversations and offers some valuable flexibility to connect the PureData System with other PureData Systems, Hadoop, DB2, Oracle and virtually any structured data source that supports JDBC drivers.

The value of content and the ability to tap into new insights is a must have to compete in any market. Fluid Query allows you to provision data for better use by application developers, data scientists and business users. We provide the tools to build the capability to enable any user group.

fluid query connectors

What’s new in Fluid Query 1.6?

Fluid Query was released this year and is in its third “agile” release of the year. As part of NPS software, it is available at no charge to existing PureData clients, and you will find information on how to access Fluid Query 1.6 below.

This capability enables you to query more data for deeper analytics from PureData. For example, you can query data in the PureData System together with:

  • Data in IBM BigInsights or other Hadoop implementations
  • Relational data stores (DB2, 3rd party and open source databases like Postgres, MySQL, etc.)
  • Multi-generational PureData Systems for Analytics systems (“Twin Fin”, “Striper”, “Mako”)

The following is a summary of some new features in the release that all help to support your needs for insights across a range of data types and stores:

  • Generic connector for access to structured data stores that support JDBC
    This generic connector enables you to select the database of choice. Database servers and engines like Teradata, SQL Server, Informix, MemSQL and MAPR can now be tapped for insight. We’ve also provided a capability to handle any data type mismatches between differing source/target systems.
  • Support for compressed read from Big SQL on IBM BigInsights
    Now using the Big SQL capability in IBM BigInsights, you are able to read compressed data in Hadoop file systems such as Big Insights, Cloudera and Hortonworks. This adds increased flexibility and efficiency in storage, data protection and access.
  • Ability to import databases to Hadoop and append to tables in Hadoop
    New capabilities now enable you to import databases to Hadoop, as well as append data in existing tables in Hadoop. One use case for this is backing up historical data to a queryable archive to help manage capacity on the data warehouse. This may include incremental backups, for example from a specific date for speed and efficiency.
  • Support for the lastest Hadoop distributions
    Fluid Query v. 1.6 now supports the latest Hadoop distributions, including BigInsights 4.1, Hortonworks 2.5 and Cloudera 5.4.5. For Netezza software, support is now available for NPS 7.2.1 and INZA 3.2.1.

Fluid Query 1.6 can be easily downloaded from IBM Support Fix Central. I encourage you to refer to my “Getting Started” post that was written for Fluid Query 1.5 for additional tips and instructions. Note that this link is for existing PureData clients. Refer to the section below if you are not a current client.

fluid query download from fix central

Packaging and distribution

From a packaging perspective we refreshed IBM Netezza Platform Developer Software to this latest NPS 7.2.1 release to ensure the software suite is current from IBM’s Passport Advantage.

Supported Appliances Supported Software
  • N3001
  • N2002
  • N2001
  • N100x
  • C1000
  • Netezza Platform Software v7.2.1
  • Netezza Client Kits v7.2.1
  • Netezza SQL Extension Toolkit v7.2.1
  • Netezza Analytics v3.2.1
  • IBM Fluid Query v1.6
  • Netezza Performance Portal v2.1.1
  • IBM Netezza Platform Development Software v7.2.1

For the Netezza Developer Network we continue to expand the ability to easily pick up and work with non-warranted products for basic evaluation by refreshing the Netezza Emulator to NPS 7.2.1 with INZA 3.2.1. You will find a refresh of our non-warranted version of Fluid Query 1.6 and the complete set of Client Kits that support NPS 7.2.1.

NDN download button

Feel free to download and play with these as a prelude to PureData Systems for Analytics purchase or as a quick way to validate new software functionality with your application. We maintain our commitment to helping our partners working with our systems by maintaining the latest systems and software for you to access. Bring your application or solution and work to certify, qualify and validate them.

For more information,  NPS 7.2.1 and INZA 3.2.1 software, refer to my post.

Doug Daily About Doug,
Doug has over 20 years combined technical & management experience in the software industry with emphasis in customer service and more recently product management.He is currently part of a highly motivated product management team that is both inspired by and passionate about the IBM PureData System for Analytics product portfolio.

Fluid doesn’t just describe your coffee anymore … Introducing IBM Fluid Query 1.0

by Wendy Lucas

Having grown up in the world of data and analytics, I long for the days when our goal was to create a single version of the truth. Remember  when data architecture diagrams showed source systems flowing through ETL, into a centralized data warehouse and then out to business intelligence applications? Wow, that was nice and simple, right – at least conceptually? As a consultant, I can still remember advising clients and helping them to pictorially represent this reference architecture. It was a pretty simple picture, but that was also a long time ago.

While IT organizations struggled with data integration, enterprise data models and producing the single source of the truth, the lines of business grew impatient and would build their own data marts (or data silos).  We can think of this as the first signs of the requirement for user self-service. The goal behind building the consolidated, enterprise, single version of the truth never went away. Sure, we still want the ability to drive more accurate decision-making, deliver consistent reporting, meet regulatory requirements, etc. However, the ability to achieve this goal became very difficult as requirements for user self-service, increased agility, new data types, lower cost solutions, better business insight and faster time to value became more important.

Recognizing the Logical Data Warehouse

Enterprises have developed collections of data assets that each provide value for specific workloads and purposes. This includes data warehouses, data marts, operational data stores and Hadoop data stores to name a few. It is really this collection of data assets that now serves as the foundation for driving analytics, fulfilling the purpose of the data warehouse within the architecture. The Logical Data Warehouse or LDW is a term we use to describe the collection of data assets that make up the data warehouse environment, recognizing that the data warehouse is no longer just a single entity. Each data store within the Logical Data Warehouse can be built on a different platform, fit for the purpose of the workload and analytic requirements it serves.


Each data store within the Logical Data Warehouse can be built on a different platform, fit for the purpose of the workload and analytic requirements it serves.

But doesn’t this go against the single version of the truth? The LDW will still struggle to deliver on the goal behind the single version of the truth, if it doesn’t have information governance, common metadata and data integration practices in place. This is a key concept. If you’re interested in more on this topic, check out a recent webcast by some of my colleagues on the “Five Pitfalls to Avoid in Your Data Warehouse Modernization Project: Making Data Work for You.”

Unifying data across the Logical Data Warehouse

Logically grouping separate data stores into the LDW does not necessarily make our lives easier. Assuming you have followed good information governance practices, you still have data stores in different places, perhaps on different platforms. Haven’t you just made your application developers and users lives, who want self-service, infinitely more difficult? Users need the ability to leverage data across these various data stores without having to worry about the complexity of where to find it, or re-writing their applications. And let’s not forget about the needs of IT. DBAs struggle to manage capacity and performance on data warehouses while listening to Hadoop administrators brag about the seemingly endless, lower cost storage and ability to manage new data types that they can provide. What if we could have the best of all worlds? Provide seamless access to data across a variety of stores, formats, and platforms. Provide capability for IT to manage Hadoop and Data Warehouses along-side each other in a way that leverages the strengths of both.

Introducing IBM Fluid Query

IBM Fluid Query is the capability to unify data across the Logical Data Warehouse, providing the ability to seamlessly access data in it’s various forms and locations. No matter where a user connects within the logical data warehouse, users have access to all data through the same, standard API/SQL/Analytics access. IBM Fluid Query powers the Logical Data Warehouse, giving users the ability to combine numerous types of data from various sources in a fast and agile manner to drive analytics and deeper insight, without worrying about connecting to multiple data stores, using different syntaxes or API’s or changing their application.

In its first release, IBM Fluid Query 1.0 will provide users of the IBM PureData System for Analytics the capability to access Hadoop data from their data warehouse and move data between Hadoop and PureData if needed. High performance is about moving the query to the data, not the data to the query. This provides extreme value to PureData users who want the ability to merge data from their structured data warehouse with Hadoop for powerful analytic combinations, or more in-depth analysis. IBM Fluid Query 1.0 is part of a toolkit within Netezza Platform Software (NPS) on the appliance so it’s free for all PureData System for Analytics customers.


IBM Fluid Query 1.0 will provide users of the IBM PureData System for Analytics the capability to access Hadoop data from their data warehouse and move data between Hadoop and PureData

For Hadoop users, IBM also provides IBM Big SQL which delivers Fluid Query capability. Big SQL provides the ability to run queries on a variety of data stores, including PureData System for Analytics, DB2 and many others from your IBM BigInsights Hadoop environment. Big SQL has the ability to push the query to the data store and return the result to Hadoop without moving all the data across the network. Other Hadoop vendors provide the ability to write queries like this but they move all the data back to Hadoop before filtering, applying predicates, joining, etc. In the world of big data, can you really afford to move lots of data around to meet the queries that need it?

IBM Fluid Query 1.0 is generally available on March 27 as a software addition to PureData System for Analytics customers. If you are an existing customer and want to understand how to take advantage of IBM Fluid Query 1.0 or if you just would like more information, I encourage you to listen to this on-demand webcast: Virtual Enzee – The Logical Data Warehouse, Hadoop and PureData System for Analytics  and check out the solution brief. Or if you are an existing PureData System for Analytics customer, download this software. Update: Learn about Fluid Query 1.5, announced July, 2015.

About Wendy,

Wendy LucasWendy Lucas is a Program Director for IBM Data Warehouse Marketing. Wendy has over 20 years of experience in data warehousing and business intelligence solutions, including 12 years at IBM. She has helped clients in a variety of roles, including application development, management consulting, project management, technical sales management and marketing. Wendy holds a Bachelor of Science in Computer Science from Capital University and you can follow her on Twitter at @wlucas001

What the Future Holds for the Database Administrator (DBA)

By Rich Hughes,

Scanning the archives as far back as 2000 reveals articles speculating on the future of the DBA.  With mounting operational costs attributed to the day-to-day maintenance of data warehouses, even 15 years ago, this was a fair question to ask.  The overhead of creating indexes, tuning individual queries, on top of the necessary nurturing of the infrastructure had many organizations looking for more cost effective alternatives.

Motivated to fix the I/O bottleneck that traditionally handicapped data warehouses, and inspired by the design goals of reduced administration and easy data access for users, the data warehouse appliance was born.  Netezza built the original data warehouse appliance that by brilliantly applying hardware and software combinations, brought the query request much closer to the data.  This breakthrough paved the way for lower administrative costs and forced others in the data warehouse market to think of additional ways to solve the I/O problem.

To be sure, Netezza disruptive technology of no indexing, great performance, and ease of administration, left many DBAs feeling threatened.  But what was really threatened was the frustrating and never ending search for data warehouse performance via indexing.  Netezza DBAs got their nights and weekends back, and adjusted by making themselves more valuable to their organizations by using the time saved with no-indexing to get closer to the business.  Higher level skills taken on by DBAs included data stewardship and data modeling, and in this freer development environment, advanced analytics took root.  In the data warehouse appliance world, much more DBA emphasis was placed on the business applications because the infrastructure was designed to run for the most part, unassisted.

Fast forward to current day where the relentless pursuit of IT cost efficiencies while providing more business value continues.  Disruptive technologies in the past decade have been invented to fill this demand, like the Hadoop Ecosystem and the maturing Cloud computing environment.  Hardware advances have pushed in-memory computing, Solid State Drives are in the process of phasing out spinning disk storage, and 128 bit CPUs and operating systems are on the drawing boards.  Databases like IBM’s dashDB have benefitted by incorporating several of these newer hardware and software advances

So 15 years into the new Millennium what’s a DBA to do? Embrace change and realize there is plenty of good news and much data to administer.  While the Cloud’s Infrastructure and Platform services will decrease on-premise DBA work over time, the added complexity will demand new solutions for determining the right mixture of on, off, and hybrid premise platforms.  Juggling the organizational data warehouse work load requires different approaches if the Cloud’s elasticity and cheaper off-hour rates are to be leveraged.

Capacity planning and data retention take on new meaning in a world where, while it is now possible to store and access everything, what is the return value of all that information? The DBA will be involved in cataloging the many new data sources as well as getting a handle on the unstructured data provided by the Internet of Things.  Moving data, when to move data, to persist or not, how does this data interact with existing schemas are all good questions to be considered for the thoughtful DBA.  And that is just on the ingest side of the ledger.  Who gets access, what are the security levels, how can applications be rapidly developed, how does one re-use SQL in a NoSQL world, and how to best federate all this wonderful data are worthwhile areas for reasonable study.

In summary, the role of the Database Administrator has always been evolving, forced by technology advances and rising business demands.  The DBA has and will continue to be one that requires general knowledge of several IT disciplines, with the opportunity to specialize.  Historically the DBA, by keeping current, can go deeper in a particular technology– a move that benefits both their career and their organization’s needs.  The DBA can logically move into an architecture or Data Scientist position, the higher skill sets for today’s world.  What has not changed is the demand to deliver reliable, affordable, and valuable information.

About Rich Hughes,

Rich Hughes is an IBM Marketing Program Manager for Data Warehousing.  Hughes has worked in a variety of Information Technology, Data Warehousing, and Big Data jobs, and has been with IBM since 2004.  Hughes earned a Bachelor’s degree from Kansas University, and a Master’s degree in Computer Science from Kansas State University.  Writing about the original Dream Team, Hughes authored a book on the 1936 US Olympic basketball team, a squad composed of oil refinery laborers and film industry stage hands. You can follow him on @rhughes134

The Combined Value of IBM Cognos and PureData System for Analytics

By Rich Hughes,

“A picture is worth a thousand words” is an adage that has weathered the test of time.  Other than noting this blog runs only about 600 words, the old saying captures the essence of modern visualization where complex data sources and entity interactions can be meaningfully refined into a single picture.  And now there are better ways to convert your data analysis into the most effective visual representation.  IBM Cognos® is quite helpful in this regard, providing the RAVE system, a platform which enables business users to develop appealing data graphics.

IBM’s Rapidly Adaptive Visualization Engine (RAVE) requests input and interaction from the user on how the graphical picture should look.  Based on IBM patented technology and concepts outlined in Wilkinson’s The Grammar of Graphics, RAVE produces the best visualization for the described circumstances. One could think of RAVE as a user productivity tool, and as an extension of the IBM Cognos Business Intelligence (BI) basic charter: insulating the business user from the nitty gritty of both SQL optimization and maximizing performance from relational databases.

For data to be useful, business users must feel comfortable working with integrated business data like finance, sales, product, and marketing entities.  Becoming routine is the further interweaving of social media, demographic, and competitor information to gain a complete view of one’s customer base.  The IBM® PureData™ System for Analytics is the appliance standard for simply delivering this type of integrated data warehouse.

IBM Cognos®, combined with PureData System for Analytics, provides leading business intelligence and enterprise scalability for reporting, interactive analysis, scorecards, and dashboards. As hinted earlier, IBM Cognos® out-of-the-box, supplies 25 data visualization graphics like Treemap, Waterfall, and Bubble charts.  IBM Cognos® will push these stunning business intelligence images out to mobile devices. IBM Cognos BI exploits Netezza analytic in-database functions, and improves upon the PureData System for Analytics by adding in-memory and caching techniques on top of fast appliance performance.

Blue Cross Blue Shield of Massachusetts (BCBSMA) is a great example of leveraging both Cognos and PureData System for Analytics.  Serving nearly 3,000,000 members from its Boston headquarters, BCBSMA uses this technology to imbed analytics into their day-to-day processes for a wide range of decision makers.  PureData System for Analytics fits the bill for a fast performing, centralized data warehouse by creating health informatics cubes in around six hours, an improvement of about 500%. This speed advantage enabled Cognos BI queries to deliver cubes with more dimensions, which thereby answered more business questions.

Blue Cross Blue Shield of Massachusetts medical directors are now able to ascertain different disease category levels at participating hospitals.  Using current and historical data, trends are spotted—providing the opportunity to actively intervene.  Benefits and care management can be designed based on this data analysis:  members with high cholesterol needed, and got help with specific programs aimed at reducing their risk of developing more serious heart problems.  Data driven decisions, a more informed and involved business community, and better health outcomes for its members are significant results from BCBSMA utilizing IBM Cognos® and PureData System for Analytics.

More information on the IBM® PureData™ System for Analytics N3001 family can be viewed at this LINK.    Included with the IBM PureData System for Analytics N3001, which was announced for General Availability on October 17, 2014, are IBM Cognos® Business Intelligence 10.2.1 software entitlements for five analytics user licenses and one analytics administrator license; these licenses can then be used when the IBM® PureData System for Analytics N3001 is your analytics data source. Particulars on Cognos combined with PureData System for Analytics will be found HERE, while Cognos BI details can be located at this URL.  A fuller treatment of the BCBSMA technology can be found on this link: BlueCross BlueShield of Massachusetts . The IBM® PureData™ System for Analytics N3001 is again changing the game for data warehouse appliances.

Figure 1: A Waterfall chart shows cumulative effects of values over time.
Figure 1: A Waterfall chart shows cumulative effects of values over time.
Figure 2: Treemaps reveal exceptions and patterns using size and color.
Figure 2: Treemaps reveal exceptions and patterns using size and color.

About Rich Hughes,

Rich Hughes is an IBM Marketing Program Manager for Data Warehousing.  Hughes has worked in a variety of Information Technology, Data Warehousing, and Big Data jobs, and has been with IBM since 2004.  Hughes earned a Bachelor’s degree from Kansas University, and a Master’s degree in Computer Science from Kansas State University.  Writing about the original Dream Team, Hughes authored a book on the 1936 US Olympic basketball team, a squad composed of oil refinery laborers and film industry stage hands. You can follow him on @rhughes134

Data Warehousing – No assembly required

By Wendy Lucas,

In my last blog, I wrote about how big things come in small packages when talking about the great value that comes in the new PureData System for Analytics Mini Appliance.  I must be in the holiday spirit early because I’m going to stick with the holiday theme for this discussion.

Did youWL 1 ever receive a gift that had multiple components to it, maybe one that required a bunch of assembly before you got to truly enjoy the gift?   I’m not talking about Lincoln Logs (do they still sell those?) or Legos where the assembly is half the fun.

I’m talking about things like a child’s bicycle that comes with the frame, handle bar, wheels, tires, kickstand, seat, nuts and bolts as a bunch of parts inside a box.

What is more exciting? Receiving a box of parts or receiving the shiny red bicycle already assembled and ready to take for an immediate ride?

WL 2

In this world where we require instant satisfaction and immediate results, we don’t have time to assemble the bike. Do your system administrators have time to custom build a solution of hardware and software for your data warehouse?  Forget about that hardware and software being truly designed, integrated and optimized for analytic workloads.  What value are your users getting while the IT staff are doing that?  Do your DBAs have enough time to tune the system for every new data source that’s added or every new report requirement that one of your users needs?  We live in a world that demands agile response to changing requirements and immediate results.

Simple is still better for faster deployment

In this very complex world, simple solutions are better.  Just like the child preferring the bike that is already assembled and ready to go, the IBM PureData System for Analytics, powered by Netezza technology has been delivering on the promise of simplicity and speed for over a decade.  Don’t just take my word for it.  In a recent study, International Technology Group compared costs and time to value with PureData compared to both Teradata and Oracle.[i]   They researched customers deploying all three solutions and had some notable findings.  While over 75% of PureData customers deployed their appliances in under 3 weeks, not a single Teradata customer deployed in that same time frame and only one Oracle customer achieved that window.

Simple is still better for lower costs

Not only is the data warehouse appliance simple to deploy but it is architected for speed with minimal tuning or administration.  The same studies found that Teradata has 3.8x and Oracle 3.5x higher deployment costs than PureData System for Analytics and use more DBA resources to maintain the system.

Simple is still better, and now even more secure

The PureData System for Analytics N3001 series that was just announced has the same speed and simplicity of it’s predecessors, but adds improved performance, self-encrypting drives and big data and business intelligence starter kits.  The self-encrypting drives encrypt all user and temp data for added security without any performance overhead or incremental cost to the appliance.

For more anecdotal examples of why simple is still better, watch this video or you can read this white paper or visit ibm.com/software/data/puredata/analytics/ for more information.

[i] ITG: Comparing Costs and Time to Value with Teradata Data Warehouse Appliance, May 2014.

ITG: Comparing Costs and Time to Value with Oracle Exadata Database Machine X3, June 2014.

About Wendy,

Wendy Lucas is a Program Director for IBM Data Warehouse Marketing. Wendy has over 20 years of experience in data warehousing and business intelligence solutions, including 12 years at IBM. She has helped clients in a variety of roles, including application development, management consulting, project management, technical sales management and marketing. Wendy holds a Bachelor of Science in Computer Science from Capital University and you can follow her on Twitter at @wlucas001